In order to overcome these inference limitations while maintaining a robust performance in terms of tool segmentation results, we propose a new approach based on YOLACT++ [1]} equipped with attention modules on the multi-scale outputs of the CNN backbone and Feature Pyramid Network (FPN). The increased representation power achieved by using attention allows the extraction of more discriminant features while suppressing the less effective ones.
